Research of Computed Tomography Inversion Algorithm for Coal Face Based on Ground Penetrating Radar

DOI

10.2991/isccca.2013.172How to use a DOI?

Keywords

GPR, CT inversion, sparse matrix, coal face, disaster sources

Abstract

Currently, mine safety is the focal point in mining activity. As a new and advanced approach for geophysical prospecting, the ground penetrating radar (GPR) is used in the mine disaster detection. Aiming to solve the restriction of low resolution and limited depth of the GPR in the deep coal seam detection, the computed tomography (CT) technology is employed for deep disaster detection in this paper. A large number of coal seam digital simulation model, including different internal diseases, are established, and the simulation data are processed by using the Least Square QR-factorization (LSQR) inversion algorithm, which has the good performance in saving computational time and memory space. Additionally, the influences of iteration precision and grid size on the effect of inversion are analyzed. The inversion results show good agreements with simulation model feature configurations, and the diseases objects can be detected.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Feng Yang
AU  - Cui Du
AU  - Meng Peng
AU  - Zequan Feng
AU  - Yangyang Sun
AU  - Enlai Li
PY  - 2013/02
DA  - 2013/02
TI  - Research of Computed Tomography Inversion Algorithm for Coal Face Based on Ground Penetrating Radar
BT  - Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013)
PB  - Atlantis Press
SP  - 686
EP  - 689
SN  - 1951-6851
UR  - https://doi.org/10.2991/isccca.2013.172
DO  - 10.2991/isccca.2013.172
ID  - Yang2013/02
ER  -